Quantifying Information Flow in Chemical Reaction Networks

被引:2
|
作者
Kahramanogullari, Ozan [1 ,2 ]
机构
[1] Univ Trento, Dept Math, Trento, Italy
[2] Univ Trento, Micrososft Res, Ctr Computat & Syst Biol, Rovereto, Italy
关键词
Chemical reaction networks; Stochastic simulation; Flux; STOCHASTIC SIMULATION; FLUCTUATIONS; ABUNDANCE; SYSTEMS;
D O I
10.1007/978-3-319-58163-7_11
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
We introduce an efficient algorithm for stochastic flux analysis of chemical reaction networks (CRN) that improves our previously published method for this task. The flux analysis algorithm extends Gillespie's direct method, commonly used for stochastically simulating CRNs with respect to mass action kinetics. The extension to the direct method involves only book-keeping constructs, and does not require any labeling of network species. We provide implementations, and illustrate on examples that our algorithm for stochastic flux analysis provides a means for quantifying information flow in CRNs. We conclude our discussion with a case study of the biochemical mechanism of gemcitabine, a prodrug widely used for treating various carcinomas.
引用
收藏
页码:155 / 166
页数:12
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